La recerca s'articula en dues línies amb els objectius que es detallen a continuació.

Percepció i Manipulació:
1. Enllaçar percepció i acció utilitzant mètodes geomètrics i estadístics per al modelatge de l'entorn i del propi robot, per a la planificació de tasques i moviments, i per a l'aprenentatge.
2. Aprofundir en l'aprenentatge per reforçament i en l'aprenentatge per demostració, en particular el "mestratge", com a base per a la interacció entre robots, humans i l'entorn.

Cinemàtica i Disseny de Robots:
3. Trobar mètodes generals i complets per a l'anàlisi i la planificació de moviments lliures de col·lisió de mecanismes.
4. Desenvolupar noves estructures mecàniques, preferentment robots paral·lels i robots basats en estructures "tensegrity".
5. Incrementar i millorar l'expertesa del grup en l'àrea del disseny mecànic

http://futur.upc.edu/ROBiri


La investigación se articula en dos líneas con los objectivos que se detallan a continuación.

Percepción y Manipulación:
1. Enlazar percepción y acción utilitzando métodos geométricos y estadísticos para el modelado del entorno y del propio robot, para la planificación de tareas y movimientos, y para el aprendizaje.
2. Profundizar en el aprendizaje por refuerzo y en el aprendizaje por demostración, en particular el entrenamiento, como base para la interacción entre robots, humanos y el entorno.

Cinemática y Diseño de Robots:
3. Encontrar métodos generales y completos para análisis y planificación de movimientos libres de colisión.
4. Desarrollar nuevas estructuras mecánicas, preferentmente robots paralelos y robots "tensegrity".
5. Incrementar y mejorar la competencia del grupo en el área del diseño mecánico.

http://futur.upc.edu/ROBiri


Research is organized in two lines with the following goals.

Perception and Manipulation:
1. Linking perception and action using geometric and statistic methods for modelling the environment and the robot, for task and motion planning, and for learning.
2. Deepening on reinforcement learning and in learning by demonstration, in particular "coaching", as a basis for the interaction of robots, humans and the environtment.

Kinematics and Robot Design:
3. Finding general and complete methods for the analysis of mechanisms and for planning collision-free motions.
4. Developing new mechanical structures, especially parallel robots and robots based on tensegrity structures.
5. Increasing and enhancing the expertise of the group in the area of mechanical design.

http://futur.upc.edu/ROBiri


Research is organized in two lines with the following goals.

Perception and Manipulation:
1. Linking perception and action using geometric and statistic methods for modelling the environment and the robot, for task and motion planning, and for learning.
2. Deepening on reinforcement learning and in learning by demonstration, in particular "coaching", as a basis for the interaction of robots, humans and the environtment.

Kinematics and Robot Design:
3. Finding general and complete methods for the analysis of mechanisms and for planning collision-free motions.
4. Developing new mechanical structures, especially parallel robots and robots based on tensegrity structures.
5. Increasing and enhancing the expertise of the group in the area of mechanical design.

http://futur.upc.edu/ROBiri

Enviaments recents

  • Database for 3D human pose estimation from single depth images 

    Arduengo García, Miguel; Alenyà Ribas, Guillem; Moreno-Noguer, Francesc (2016)
    Report de recerca
    Accés obert
    This work is part of the project I-­-DRESS (Assistive interactive robotic system for support in dressing). The specific objective is the detection of human body postures and the tracking of their movements. To this end, ...
  • Deciding the different robot roles for patient cognitive training 

    Andriella, Antonio; Alenyà Ribas, Guillem; Hernández Farigola, Joan; Torras, Carme (2018-09-01)
    Article
    Accés restringit per política de l'editorial
    Alzheimer’s Disease (AD) and Mild Cognitive Impairment (MCI) represent a major challenge for health systems within the aging population. New and better instruments will be crucial to assess the disease severity and ...
  • Breakingnews: article annotation by image and text processing 

    Ramisa Ayats, Arnau; Yan, Fei; Moreno-Noguer, Francesc; Mikolajczyk, Krystian (Institute of Electrical and Electronics Engineers (IEEE), 2018-05-01)
    Article
    Accés obert
    Building upon recent Deep Neural Network architectures, current approaches lying in the intersection of Computer Vision and Natural Language Processing have achieved unprecedented breakthroughs in tasks like automatic ...
  • Teaching a robot the semantics of assembly tasks 

    Savarimuthu, Thiusius Rajeeth; Anders, Buch; Schlette, Christian; Wantia, Nils; Rossmann, Jürgen; Martinez Martinez, David; Alenyà Ribas, Guillem; Torras, Carme; Ales, Ude; Bojan, Nemec; Aljaž, Kramberger; Worgotter, Florentin; Eren Erdal, Aksoy; Papon, Jeremie; Haller, Simon; Piater, Justus; Krüger, Norbert (Institute of Electrical and Electronics Engineers (IEEE), 2018)
    Article
    Accés obert
    We present a three-level cognitive system in a learning by demonstration context. The system allows for learn- ing and transfer on the sensorimotor level as well as the planning level. The fundamentally different data ...
  • A scalable, efficient, and accurate solution to non-rigid structure from motion 

    Agudo Martínez, Antonio; Moreno-Noguer, Francesc (2018)
    Article
    Accés obert
    Most Non-Rigid Structure from Motion (NRSfM) solutions are based on factorization approaches that allow reconstructing objects parameterized by a sparse set of 3D points. These solutions, however, are low resolution and ...
  • Robot motion adaptation through user intervention and reinforcement learning 

    Jevtic, Aleksandar; Colomé Figueras, Adrià; Alenyà Ribas, Guillem; Torras, Carme (Elsevier, 2018-04-01)
    Article
    Accés obert
    Assistant robots are designed to perform specific tasks for the user, but their performance is rarely optimal, hence they are required to adapt to user preferences or new task requirements. In the previous work, the potential ...
  • Task-driven active sensing framework applied to leaf probing 

    Foix Salmerón, Sergi; Alenyà Ribas, Guillem; Torras, Carme (2018-04-01)
    Article
    Accés obert
    This article presents a new method for actively exploring a 3D workspace with the aim of localizing relevant regions for a given task. Our method encodes the exploration route in a multi-layer occupancy grid map. This map, ...
  • Teaching robot's proactive behavior using human assistance 

    Garrell Zulueta, Anais; Villamizar Vergel, Michael Alejandro; Moreno-Noguer, Francesc; Sanfeliu Cortés, Alberto (2017-04-01)
    Article
    Accés obert
    In recent years, there has been a growing interest in enabling autonomous social robots to interact with people. However, many questions remain unresolved regarding the social capabilities robots should have in order to ...
  • Adaptable multimodal interaction framework for robot-assisted cognitive training 

    Taranovic, Aleksandar; Jevtic, Aleksandar; Torras, Carme (2018)
    Text en actes de congrés
    Accés obert
    The size of the population with cognitive impairment is increasing worldwide, and socially assistive robotics offers a solution to the growing demand for professional carers. Adaptation to users generates more natural, ...
  • Dimensionality reduction for dynamic movement primitives and application to bimanual manipulation of clothes 

    Colomé Figueras, Adrià; Torras, Carme (Institute of Electrical and Electronics Engineers (IEEE), 2018)
    Article
    Accés obert
    Dynamic Movement Primitives (DMPs) are nowadays widely used as movement parametrization for learning robot trajectories, because of their linearity in the parameters, rescaling robustness and continuity. However, when ...
  • Active garment recognition and target grasping point detection using deep learning 

    Corona Puyane, Enric; Alenyà Ribas, Guillem; Gabas Nova, Antonio; Torras, Carme (2018-02-01)
    Article
    Accés obert
    Identification and bi-manual handling of deformable objects, like textiles, is one of the most challenging tasks in the field of industrial and service robotics. Their unpredictable shape and pose makes it very difficult ...
  • Learning depth-aware deep representations for robotic perception 

    Porzi, Lorenzo; Rota Bulò, Samuel; Peñate Sánchez, Adrián; Ricci, Elisa; Moreno-Noguer, Francesc (Institute of Electrical and Electronics Engineers (IEEE), 2017)
    Article
    Accés obert
    Exploiting RGB-D data by means of Convolutional Neural Networks (CNNs) is at the core of a number of robotics applications, including object detection, scene semantic segmentation and grasping. Most existing approaches, ...

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